¶ Elastic Security SIEM with Elasticsearch
¶ Cyber security
There’s a moment in every cybersecurity journey when you realize that logs are not just byproducts of systems—they are fragments of stories. Each authentication attempt, each network connection, each process execution, each anomaly whispered by a machine is a clue in a much larger investigation. The challenge isn’t gathering these clues; modern systems emit them endlessly. The real challenge is making sense of them. Understanding how they connect. Seeing the patterns buried under mountains of noise. This is where SIEMs began, and where Elastic Security—powered by Elasticsearch—has changed the landscape entirely.
In the earlier days of security operations, logs were something you skimmed through during incidents or compliance audits. They were static, scattered, stubborn. Then attacks grew more sophisticated, more persistent, more subtle. Suddenly, monitoring wasn’t enough. Teams needed visibility—real visibility—across every corner of their digital ecosystem. They needed to correlate events across hosts, networks, cloud services, containers, identities, applications, and unknown places in between. They needed speed, scale, and context.
Elastic Security, built on the Elasticsearch platform, emerged in this gap. It didn’t begin as a traditional SIEM—it grew into one naturally, driven by its own strengths: search, scalability, indexing efficiency, visualization, and data flexibility. Today, Elastic Security is more than a SIEM. It’s an investigative workspace, a detection engine, an endpoint defense platform, and a unification layer between raw data and human insight.
This course is a journey through that world—through the ideas, practices, and evolving techniques that shape how Elastic Security helps defenders understand, detect, and respond to threats.
What makes Elastic Security compelling is that it doesn’t feel like a closed system. It feels open, adaptable, and responsive. Elasticsearch, at its core, is a search engine designed for speed and scale. But search in cybersecurity isn’t just about finding a log entry—it’s about slicing through terabytes of data to uncover relationships that would otherwise stay invisible. When analysts run a query, they aren’t searching for a string—they’re searching for truth: the root cause, the chain of events, the hidden foothold. Elasticsearch turns that search into something immediate and intuitive.
Before SIEM became a buzzword, detection used to rely heavily on signatures. You waited for a known threat to reveal itself in a predictable way. But attackers didn’t play along. They adapted fast, they reused infrastructure in clever ways, they blended into legitimate traffic. Modern SIEMs had to evolve into something smarter, something capable of behavior-based detection and correlation. Elastic Security answered this with rule engines that combine precision and flexibility. You can write rules that detect patterns across events, across timeframes, across hosts—rules that look for behaviors, not just artifacts.
This is where analysts begin to appreciate the platform. Instead of guessing which logs might contain a clue, they can use the SIEM to surface unusual sequences: a suspicious login followed by privilege escalation, or a cluster of failed authentication attempts across multiple services, or an encoded PowerShell command, or a connection to a domain newly seen in threat-intelligence feeds. Elastic Security weaves these pieces together, and suddenly detection becomes more about reasoning and less about luck.
One of the core strengths of Elastic Security is its emphasis on unifying endpoint and SIEM capabilities. This integration wasn’t an afterthought; it was a response to the way real attackers behave. They don’t just attack networks; they attack hosts. They don’t just leave traces in logs; they leave traces in memory, processes, file changes, registry modifications, and user actions. By wrapping endpoint protection and detection around the SIEM, Elastic created a platform where context naturally flows from one layer to another. An alert raised from a suspicious process can lead directly into historical log analysis, threat intelligence matching, and timeline reconstruction.
That timeline view—the sequence of events leading up to an incident—is where analysts feel the platform come alive. Logs become a narrative. What happened first? What triggered what? How did privilege escalate? Where did persistence appear? With Elastic Security, the timeline is not just text on a screen; it becomes an interactive map of an attack’s anatomy. It guides investigations, and it encourages the analyst to follow threads that might otherwise be overlooked.
Another dimension of Elastic Security is how gracefully it scales. Modern infrastructures aren’t static. They span clouds, regions, containers, dynamic instances, ephemeral workloads. Logs multiply exponentially. Traditional SIEMs struggled in this environment—either they became too slow or too expensive. Elasticsearch, built from the ground up for distributed indexing and search, feels like it was designed precisely for this era. It lets organizations handle enormous event volumes without sacrificing performance or clarity. And because it’s built on open principles, teams can shape the system to fit their environment instead of shaping their environment to fit the system.
One of the most interesting aspects you’ll explore in this course is how Elastic Security encourages defenders to think like investigators. Not every detection should result in panic. Some detections are part of broader patterns. Some are false-positive signals in disguise. Some are early warnings long before a true compromise begins. The platform’s approach to security operations encourages triage, correlation, and thoughtful response. It doesn’t overwhelm analysts; it guides them.
At the same time, Elastic Security encourages creativity. Writing custom queries feels almost natural. Crafting correlation rules becomes an exercise in expressing logic rather than fighting syntax. Visualizing results with Kibana dashboards transforms abstract data into patterns you can almost feel. Analysts begin to recognize behaviors visually: a sudden spike in DNS requests, unusual outbound traffic from a single host, repeated file access attempts from an unknown process. Visualization brings intuition into the workflow.
Threat intelligence becomes another layer in this ecosystem. Instead of relying on isolated indicators, Elastic Security pulls intelligence feeds directly into the platform. Domains, IPs, hashes, actor profiles, campaign mappings—they become part of the detection logic, enriching events so analysts can understand whether an unusual connection is merely noisy or tied to known malicious infrastructure. When new intelligence arrives, Elastic Security makes it part of your defensive muscle almost instantly.
A recurring theme throughout this course will be how Elastic Security changes the role of the SOC. Instead of being overwhelmed by events, analysts gain clarity. Instead of drowning in alerts, they see priorities. Instead of reacting endlessly, they begin to anticipate patterns. Detection turns proactive. Response becomes faster. Hunting becomes routine rather than exceptional. It’s not that Elastic Security solves every challenge—it’s that it equips analysts with the flexibility, speed, and visibility needed to approach challenges intelligently.
You’ll also explore how Elastic Security fits into modern security frameworks like MITRE ATT&CK. Integrating tactics and techniques into detections allows the platform to reason about adversary behavior in a structured way. Analysts can see which parts of the kill chain are lighting up. They can identify whether an attacker is probing, escalating, persisting, or exfiltrating. These insights allow organizations to focus remediation efforts in exactly the right places.
As you progress through these articles, you’ll dive deeper into ingestion pipelines, parsing, normalization, mapping fields with ECS, designing detection rules, building dashboards, conducting threat hunting, orchestrating responses, scaling clusters, analyzing queries, identifying anomalies with machine learning, and weaving all these components into a unified defensive strategy. You’ll see how each part strengthens the others and how the entire platform becomes far more than the sum of its pieces.
Perhaps the most important thing you’ll take away is the mindset that Elastic Security encourages. It pushes you to stop thinking in terms of logs and start thinking in terms of stories. It encourages you to see indicators not as isolated data points but as relationships. It teaches you to expect patterns, to trust your observations, to follow intuition, to verify with data. And once you internalize this mindset, your entire approach to cybersecurity transforms.
By the time you complete this course, Elastic Security with Elasticsearch won’t feel like a collection of tools. It will feel like an environment where your thoughts as an analyst can be expressed naturally. You’ll understand how to shape data, how to investigate meaningfully, how to detect proactively, and how to use the strengths of the platform to amplify your own reasoning.
Cybersecurity is not merely a technical discipline. It’s an ongoing dialogue between defenders and adversaries. Elastic Security allows defenders to engage in that dialogue with confidence, insight, and clarity. And this course is your invitation to explore that world deeply—one query, one log, one investigation at a time.
Let’s begin the journey.
¶ Elastic Security SIEM with Elasticsearch
¶ Beginner (Chapters 1-20)
1. Introduction to Cybersecurity and the Importance of SIEM
2. What is Elastic Security SIEM and How Does it Work?
3. Overview of Elasticsearch and Its Role in SIEM
4. Installing and Setting Up Elastic Security SIEM
5. Understanding the Elastic Stack: Elasticsearch, Kibana, Logstash, and Beats
6. Navigating the Elastic Security User Interface
7. Getting Started with Elasticsearch and Kibana for Security Monitoring
8. Basics of Log Collection and Parsing in Elastic Security
9. Understanding Elasticsearch Indexing and Storage Mechanisms
10. Configuring Elastic Agents and Beats for Data Collection
11. Introduction to Elastic Security Dashboards and Visualization
12. Basic Querying in Elasticsearch: Using KQL and Lucene Query Language
13. Elastic Security Overview: Detection, Investigation, and Response
14. Introduction to Alerts and Rule Management in Elastic Security
15. Configuring Elasticsearch Cluster for Security Monitoring
16. Elastic Security’s Role in Detecting and Mitigating Threats
17. Collecting and Parsing Network Data for Threat Detection in Elastic Security
18. Implementing Basic Detection Rules in Elastic Security SIEM
19. Elastic Security Timeline: How to Investigate Incidents
20. Introduction to Elasticsearch’s Full-Text Search for Security Monitoring
¶ Intermediate (Chapters 21-60)
21. Advanced Installation and Configuration of Elastic Security
22. Deploying Elastic Security in Multi-Tier and Cloud Environments
23. Data Ingestion: Configuring Beats, Logstash, and Filebeat
24. Setting Up and Managing Elasticsearch Indices for SIEM Data
25. Creating Custom Dashboards in Kibana for Security Monitoring
26. Advanced Searching Techniques in Elasticsearch
27. Defining and Creating Detection Rules in Elastic Security
28. Using Elastic Security for Real-Time Threat Detection
29. Automating Response Actions in Elastic Security SIEM
30. Integrating Elastic Security with Other Security Tools and Platforms
31. Elastic Security and Threat Intelligence: Integration and Best Practices
32. Using Elastic Security for Monitoring Endpoint Security
33. Leveraging Elastic’s Machine Learning Features for Anomaly Detection
34. Analyzing and Visualizing Security Events in Kibana
35. Using the Elastic Security Data Explorer for Incident Investigation
36. Managing Users and Roles in Elastic Security SIEM
37. Elastic Security Querying: Using KQL for Efficient Search and Analysis
38. Configuring and Managing Alerts in Elastic Security
39. Understanding and Using Elastic Security’s Alerting Framework
40. Detecting and Investigating Suspicious Network Traffic in Elastic Security
41. Using Elastic Security for Log Analysis and Event Correlation
42. Building Effective Security Dashboards with Kibana
43. Handling False Positives and Tuning Detection Rules in Elastic Security
44. Configuring and Using Elastic Security for Compliance Audits
45. Setting Up and Using Elastic Security’s SIEM Detection Engine
46. Investigating and Responding to Security Incidents Using Elastic Security
47. Using Elastic Security to Detect and Prevent Phishing Attacks
48. Managing Alerts and Notifications in Elastic Security
49. Creating and Managing Custom Detection Rules in Elastic Security
50. Integrating Elastic Security with Threat Intelligence Feeds
51. Performing Network Traffic Analysis with Elastic Security
52. Using Elastic Security to Detect Lateral Movement in Networks
53. Elastic Security and Cloud Security Monitoring: Best Practices
54. Configuring File Integrity Monitoring with Elastic Security
55. Enhancing Security Operations with Elastic Security SIEM
56. Using Elastic Security for Vulnerability Management
57. Using Elasticsearch for Event Log Analysis in Cybersecurity
58. Leveraging Elastic Security to Detect Insider Threats
59. Implementing Log Management and Retention Policies in Elastic Security
60. Scaling Elastic Security to Handle Large-Scale Security Data
¶ Advanced (Chapters 61-100)
61. Optimizing Elasticsearch for Security Use Cases
62. Customizing Elasticsearch for Advanced Threat Detection
63. Using Elastic Security in a Distributed or Hybrid Cloud Environment
64. Elasticsearch Query Optimization for Security Analytics
65. Building Complex Detection Rules with Elasticsearch Query DSL
66. Advanced Machine Learning Techniques in Elastic Security SIEM
67. Integrating Elasticsearch with External Data Sources for Threat Detection
68. Fine-Tuning Elasticsearch Indexing for SIEM Data
69. Elastic Security for Red Team and Penetration Testing Exercises
70. Configuring Elastic Stack for Real-Time Threat Detection and Response
71. Elastic Security for Security Operations Centers (SOC)
72. Investigating Security Incidents in Elastic Security with Advanced Kibana Features
73. Using Kibana for Advanced Forensics and Root Cause Analysis
74. Threat Hunting Using Elastic Security’s Query Capabilities
75. Automating Incident Response with Elastic Security SIEM
76. Building an Elastic Security SIEM Architecture for Enterprise Environments
77. Configuring Elasticsearch for Multi-Tenant Environments in Security Operations
78. Using Elastic Security for Deception and Honeypot Monitoring
79. Securing Elastic Security: Access Control and Authentication Best Practices
80. Advanced Elastic Security Querying: Complex Patterns and Anomalies
81. Leveraging Elastic Security for Compliance Frameworks (e.g., NIST, GDPR)
82. Elastic Security in a Zero Trust Architecture
83. Security Data Visualization with Kibana: Advanced Techniques
84. Real-Time Attack Surface Monitoring with Elastic Security
85. Advanced Detection Techniques Using Machine Learning in Elastic Security
86. Elastic Security for Threat Intelligence Enrichment
87. Building Custom Plugins and Extensions for Elastic Security
88. Advanced Use Cases for Threat Detection in Elastic Security
89. Using Elastic Security for Incident Response and Root Cause Analysis
90. Building Custom Dashboards for Threat Hunting and Investigation
91. Elastic Security for Digital Forensics and Evidence Preservation
92. Managing and Scaling Elasticsearch Clusters for Security Data
93. Integrating Elastic Security with Third-Party Security Tools
94. Elastic Security’s Role in Preventing and Detecting DDoS Attacks
95. Developing and Managing a Comprehensive Threat Detection Strategy with Elastic Security
96. Using Elastic Security for Continuous Monitoring of Cloud Environments
97. Configuring and Monitoring User Behavior Analytics (UBA) with Elastic Security
98. Integrating Elastic Security with Automated Playbooks and SOAR Platforms
99. Developing Custom Security Analytics Applications on Elasticsearch
100. The Future of SIEM: Evolving Threat Detection with Elastic Security